Associate, AI & Data Engineering

Job Overview

Role: Associate, AI & Data Engineering Location: Bangalore Experience: 0-2 Years Qualification: Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field. Key Skills: Artificial Intelligence, Generative AI, Data Engineering, AI platforms, Cloud (Azure, Google Cloud), Python, TypeScript, JavaScript, Automation, MLOps, LLMOps, APIs, Vector Databases, Embeddings

Job Description

The selected candidate will work on enterprise AI and data engineering initiatives involving multiple AI platforms and cloud technologies. Key responsibilities include supporting the design, deployment, and maintenance of enterprise AI platform solutions using Microsoft Copilot, Google Gemini Enterprise, and Vertex AI. The role integrates AI platforms with various data sources and assists in developing Retrieval-Augmented Generation (RAG) pipelines.

Roles and Responsibilities

• AI Platform Solution Support: Support the design, deployment, and maintenance of enterprise AI platform solutions. Work with platforms such as Microsoft Copilot, Copilot Studio, Google Gemini Enterprise, Google Workspace, and Vertex AI.
• Integration & Data Grounding: Build and maintain enterprise connectors, plugins, and OpenAPI integrations. Integrate AI platforms with databases, ERP systems, and legacy applications. Support data grounding and retrieval solutions using Microsoft Graph and Google Cloud APIs.
• RAG Development: Assist in developing Retrieval-Augmented Generation (RAG) pipelines. Work with enterprise data and content sources such as SharePoint, OneDrive, and Google Drive.
• Automation & Agentic AI: Support the development of multi-agent workflows. Work with frameworks such as Semantic Kernel and Azure AI Agent Service. Develop Python-based orchestration solutions where required. Connect Power Platform, Power Automate, and Logic Apps with backend scripts. Support AI-powered business automation initiatives.
• AI Platform Evaluation: Participate in evaluating emerging AI platforms and technologies (e.g., Codex, Claude, Kong AI) against enterprise requirements, assessing capabilities, security, performance, and integration.
• Governance & Security: Implement AI governance and enterprise guardrails. Support Data Loss Prevention (DLP) policies. Ensure AI outputs respect user permissions and enterprise data boundaries. Work with Microsoft Entra ID and OAuth 2.0 concepts. Support regional data residency requirements.
• Monitoring & Performance: Monitoring AI usage, API latency, response quality, and cost. Building dashboards using Power BI or Looker.
• Power Platform Administration: Support Power Platform governance, managing security and DLP policies, application lifecycle management (ALM), Microsoft Purview, GitHub, and CI/CD pipelines.
• MLOps & LLMOps: Gain exposure to operationalizing machine learning and Generative AI solutions using Azure AI Foundry, Azure Monitor, Application Insights, GitHub CI/CD pipelines, and responsible AI practices.

Skills and Eligibility Criteria

Educational Background: Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.

Experience: 0–2 years of relevant experience in AI platforms, cloud engineering, automation, data platforms, or enterprise application development.

Mandatory Technical Skills:

• Basic hands-on experience with Python, TypeScript, JavaScript, or a similar programming language.
• Ability to build scripts, integrations, custom plugins, and applications using programming languages.
• Basic understanding of Generative AI, Large Language Models (LLMs), APIs and data integration, Retrieval-Augmented Generation (RAG), Prompts and prompt engineering, Embeddings, Vector databases, AI model lifecycle concepts, Data processing and ingestion.
• Familiarity with Microsoft Azure, Azure AI Foundry, Azure AI Services, Google Cloud Platform, Vertex AI, Microsoft 365, Microsoft Power Platform.
• Awareness of access control, data privacy, data security, compliance, and Responsible AI principles.
• 0–2 years of hands-on experience with Microsoft Copilot Studio, Power Platform, Google Gemini Enterprise, or Vertex AI.
• Understanding of Azure AI Foundry, Azure AI Services, and Google Cloud Platform.
• Experience or knowledge of graph data, embeddings, vector databases, and enterprise content management systems.
• Experience with continuous integration and deployment pipelines for AI agents, prompt configurations, and platform automation.

Competencies:

• Ability to learn quickly and take ownership of assigned tasks.
• Good communication and documentation skills.